A PREDICTIVE SUBSTRATE MODEL FOR RAT GLUTATHIONE-S-TRANSFERASE-4-4

Citation
Mj. Degroot et al., A PREDICTIVE SUBSTRATE MODEL FOR RAT GLUTATHIONE-S-TRANSFERASE-4-4, Chemical research in toxicology, 8(5), 1995, pp. 649-658
Citations number
45
Categorie Soggetti
Toxicology,Chemistry
ISSN journal
0893228X
Volume
8
Issue
5
Year of publication
1995
Pages
649 - 658
Database
ISI
SICI code
0893-228X(1995)8:5<649:APSMFR>2.0.ZU;2-#
Abstract
Molecular modeling techniques have been used to derive a substrate mod el for class mu rat glutathione S-transferase 4-4 (GST 4-4). Informati on on regio- and stereoselective product formation of 20 substrates co vering three chemically and structurally different classes was used to construct a substrate model containing three interaction sites respon sible for Lewis acid-Lewis base interactions (IS1, IS2, and IS3), as w ell as a region responsible for aromatic interactions (IS4). Experimen tal data suggest that the first protein interaction site (pIS(1), inte racting with IS1) corresponds with Tyr(115), while the other protein i nteraction sites (pIS(2) and pIS(3)) probably correspond with other Le wis acidic amino acids. All substrates exhibited positive molecular el ectrostatic potentials (MEPs) near the site of conjugation with glutat hione (GSH), as well as negative MEP values near the position of group s with Lewis base properties (IS1, IS2, or IS3), which interact with p IS(1), pIS(2), or pIS(3), respectively. Obviously, complementarity bet ween the MEPs of substrates and protein in specific regions is importa nt. The substrate specificity and stereoselectivity of GST 4-4 are mos t likely determined by pIS(1) and the distance between the site of GSH attack and Lewis base atoms in the substrates which interact with eit her pIS(2), pIS(3), or a combination of these sites. Interaction betwe en aromatic regions in the substrate with aromatic amino acids in the protein further stabilizes the substrate in the active site. The predi ctive value of the model has been evaluated by rationalizing the conju gation to GSH of 11 substrates of GST 4-4 (representing 3 classes of c ompounds) which were not used to construct the model. All known metabo lites of these substrates are explained with the model. As the compute r-aided predictions appear to correlate well with experimental results , the presented substrate model may be useful to identify new potentia l GST 4-4 substrates.